EEG-based Emotion Recognition Using Recurrence Plot Analysis and K Nearest Neighbor Classifier

Publish Year: 1392
نوع سند: مقاله کنفرانسی
زبان: English
View: 905

This Paper With 6 Page And PDF Format Ready To Download

  • Certificate
  • من نویسنده این مقاله هستم

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این Paper:

شناسه ملی سند علمی:

ICBME20_093

تاریخ نمایه سازی: 25 فروردین 1394

Abstract:

Electroencephalogram (EEG)-based emotion recognition has been a rapidly growing field. However, accurate and sufficient performance rates are yet to be obtained. This paper presents the classification of EEG correlates on emotion using the relatively new non-linear feature extraction method, namely, Recurrence Plot analysis to extract thirteen non-linear features. This method is compared with feature extraction method based on spectral power analysis. The K nearest neighbor is applied to classify extracted features into the emotional states based on arousal-valence (high/low arousal, valence) plane with the addition of liking axis (positive/negative). Leading to performance rates of 58.05%, 64.56% and 67.42% for 3 classes of valence, arousal and liking; which confirm the advantage of a non-linear feature extraction method over previous frequency based feature extraction techniques

Authors

Fatemeh Bahari

Department of Biomedical Engineering Amirkabir University of Technology Tehran, Iran

Amin Janghorbani

Department of Biomedical Engineering Amirkabir University of Technology Tehran, Iran